Impact Factor

Focused Review ARTICLE

Front. Neurosci., 15 September 2009 | http://dx.doi.org/10.3389/neuro.01.026.2009

The Brian simulator

Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Paris, France
Département d’Etudes Cognitives, Ecole Normale Supérieure, Paris, France
“Brian” is a simulator for spiking neural networks (http://www.briansimulator.org ). The focus is on making the writing of simulation code as quick and easy as possible for the user, and on flexibility: new and non-standard models are no more difficult to define than standard ones. This allows scientists to spend more time on the details of their models, and less on their implementation. Neuron models are defined by writing differential equations in standard mathematical notation, facilitating scientific communication. Brian is written in the Python programming language, and uses vector-based computation to allow for efficient simulations. It is particularly useful for neuroscientific modelling at the systems level, and for teaching computational neuroscience.
Python, spiking neural networks, simulation, teaching, systems neuroscience
Goodman DF and Brette R (2009). The Brian simulator.Front. Neurosci. 3,2:192- 197. doi: 10.3389/neuro.01.026.2009
22 April 2009;
 Paper pending published:
26 June 2009;
08 July 2009;
 Published online:
15 September 2009.

Edited by:

Jan G. Bjaalie, International Neuroinformatics Coordination Facility, Sweden; University of Oslo, Norway

Reviewed by:

Eilif Muller, Ecole Polytechnique Fédérale de Lausanne, Switzerland
Nicholas T. Carnevale, Yale University School of Medicine, USA
Örjan Ekeberg, Royal Institute of Technology, Sweden
© 2009 Goodman and Brette. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
Dan Goodman, Equipe Audition, Département d'Etudes Cognitives, Ecole Normale Supérieure, 29, rue d'Ulm, 75230 Paris Cedex 05, France. dan.goodman@ens.fr